A review of multivariate longitudinal data analysis

DOI10.1177/0962280209340191zbMath1270.62011OpenAlexW2077527474WikidataQ33538465 ScholiaQ33538465MaRDI QIDQ4924352

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Publication date: 31 May 2013

Published in: Statistical Methods in Medical Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/0962280209340191

Mathematics Subject Classification ID

Related Items (11)

Robust Bayesian hierarchical model using normal/independent distributions ⋮ A stochastic variant of the EM algorithm to fit mixed (discrete and continuous) longitudinal data with nonignorable missingness ⋮ Bayesian hierarchical joint modeling using skew-normal/independent distributions ⋮ The analysis of multivariate longitudinal data using multivariate marginal models ⋮ Multivariate mix-GEE models for longitudinal data with multiple outcomes ⋮ Mixed modeling with whole genome data ⋮ A transition model for analyzing multivariate longitudinal data using Gaussian copula approach ⋮ Multiple comparisons for multiple endpoints in agricultural experiments ⋮ A copula-based GLMM model for multivariate longitudinal data with mixed-types of responses ⋮ Modeling the Cholesky factors of covariance matrices of multivariate longitudinal data ⋮ Covariance pattern mixture models for the analysis of multivariate heterogeneous longitudinal data

Uses Software

• R
• SemiPar

Cites Work

• Longitudinal data analysis using generalized linear models
• Random-Effects Models for Longitudinal Data
• Bootstrap confidence intervals. With comments and a rejoinder by the authors
• Latent Transition Regression for Mixed Outcomes
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Estimating Equations for Parameters in Means and Covariances of Multivariate Discrete and Continuous Responses
• A subclass of lattice processes applied to a problem in planar sampling
• Modelling multivariate binary data with alternating logistic regressions
• Analyzing Bivariate Repeated Measures for Discrete and Continuous Outcome Variables
• A Stochastic Model for the Analysis of Bivariate Longitudinal AIDS Data
• Semiparametric Regression
• Estimating a Treatment Effect from Multidimensional Longitudinal Data
• Latent Variable Models for Longitudinal Data with Multiple Continuous Outcomes
• General class of covariance structures for two or more repeated factors in longitudinal data analysis
• Pairwise Fitting of Mixed Models for the Joint Modeling of Multivariate Longitudinal Profiles
• Joint Models for Multivariate Longitudinal and Multivariate Survival Data
• Modeling Unequally Spaced Bivariate Growth Curve Data Using a Kalman Filter Approach
• An estimator for the proportional hazards model with multiple longitudinal covariates measured with error
• Maximum Likelihood Estimation of Misspecified Models
• Linear mixed models for longitudinal data

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